Query-based channel state information feedback decoding for cross-node machine learning
AssigneeQUALCOMM Incorporated
InventorsJune NAMGOONG, Akash Sandeep DOSHI, Taesang YOO, Hyojin LEE
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Abstract
Various aspects of the present disclosure generally relate to wireless communication. In some aspects, a user equipment (UE) may receive, from a network node, a transformer configuration that includes a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more channel state information (CSI) feedback tasks of a plurality of CSI feedback tasks associated with a transformer-based cross-node machine learning system, and transmit the at least one latent vector based at least in part on instantiating the transmitter neural network. Numerous other aspects are described.
Claims20
An apparatus for wireless communication at a user equipment (UE), comprising:
- one or more memories;
- and
- one or more processors, coupled to the one or more memories, which, individually or in any combination, are operable to cause the apparatus to:
- receive a transformer configuration that includes a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more channel state information (CSI) feedback tasks of a plurality of CSI feedback tasks associated with a transformer-based cross-node machine learning system;
- and
- transmit the at least one latent vector based at least in part on instantiating the transmitter neural network.
An apparatus for wireless communication at a network entity, comprising:
- one or more memories;
- and
- one or more processors, coupled to the one or more memories, which, individually or in any combination, are operable to cause the apparatus to:
- receive a latent vector from a user equipment (UE), the latent vector corresponding to one or more channel state information (CSI) feedback tasks of a plurality of CSI feedback tasks associated with a transformer-based cross-node machine learning system;
- and
- process the received latent vector using a receiver neural network, wherein the receiver neural network includes a decoder layer that includes a self-attention layer followed by a cross-attention layer that takes a mapped CSI feedback vector as key and value.
A method of wireless communication performed by a user equipment (UE), comprising:
- receiving a transformer configuration that includes a transmitter neural network configured to be used to generate at least one latent vector corresponding to one or more channel state information (CSI) feedback tasks of a plurality of CSI feedback tasks associated with a transformer-based cross-node machine learning system;
- and
- transmitting the at least one latent vector based at least in part on instantiating the transmitter neural network.
Dependencies are inferred from the claim text.